Ganesan, T. and Elamvazuthi, I. and Shaari, K.Z.K. and Vasant, P. (2013) Multiobjective optimization of green sand mould system using chaotic differential evolution. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8160. pp. 145-163. ISSN 03029743
Full text not available from this repository.Abstract
Many industrial optimization cases present themselves in a multi-objective (MO) setting (where each of the objectives portrays different aspects of the problem). Therefore, it is important for the decision-maker to have a solution set of options prior to selecting the best solution. In this work, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms; differential evolution (DE), chaotic differential evolution (CDE) and gravitational search algorithm (GSA). These methods are then used to generate the approximate Pareto frontier to the green sand mould system problem. The Hypervolume Indicator (HVI) is applied to gauge the capabilities of each algorithm in approximating the Pareto frontier. Some comparative studies were then carried out with the algorithms developed in this work and that from the previous work. Analysis on the performance as well as the quality of the solutions obtained by these algorithms is shown here. © 2013 Springer-Verlag Berlin Heidelberg.
Item Type: | Article |
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Additional Information: | cited By 13 |
Uncontrolled Keywords: | Biomimetics; Chaos theory; Decision making; Green manufacturing; Heuristic algorithms; Learning algorithms; Molds; Multiobjective optimization, Chaotic differential evolutions; Differential Evolution; Gravitational search algorithm (GSA); Green sand mould systems; Hypervolume indicators; Industrial optimization; Multi objective; Pareto frontiers; Weighted sum approaches, Evolutionary algorithms |
Depositing User: | Mr Ahmad Suhairi UTP |
Date Deposited: | 09 Nov 2023 15:52 |
Last Modified: | 09 Nov 2023 15:52 |
URI: | https://khub.utp.edu.my/scholars/id/eprint/3903 |